ArticleJournal of diabetes science and technology2021
Prediction of Individual Basal Rate Profiles From Patient Characteristics in Type 1 Diabetes on Insulin Pump Therapy.
Article in Journal of diabetes science and technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review and Meta-Analysis of Continuous Subcutaneous Insulin Infusion vs. Multiple Daily Injections in Type-2 Diabetes.Medicina (Kaunas, Lithuania) · 2023Pooled it
- Toward a Personalized Basal Tuner for Detecting Basal Rate Inaccuracies in Type 1 Diabetes Mellitus Without Meal Data: Algorithm Development and Retrospective Validation Study.JMIR diabetes · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBasal rate profiles in patients with type 1 diabetes on insulin pump therapy are subject to enormous inter-individual heterogeneity. Tools to predict basal rates based on clinical characteristics may facilitate insulin pump therapy.
methodsData from 339 consecutive in-patients with adult type 1 diabetes on insulin pump therapy were collected. Basal rate tests were performed over 24 hours. A mathematical algorithm to predict individual basal rate profiles was generated by relating the individual insulin demand to selected clinical characteristics in an exploratory cohort of 170 patients. The predicted insulin pump profiles were validated in a confirmatory cohort of 169 patients.
findingsBasal rates (0.27 ± 0.01 IU.d
interpretationClinical characteristics predict 52% of the variation in individual basal rate profiles, including their diurnal fluctuations. The multivariate regression model can be used to initiate or optimize insulin pump treatment in patients with type 1 diabetes.
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